How can LLMs solve complex data analysis tasks?
Advanced Reasoning and Transformation Engine for Multi-Step Insight Synthesis in Data Analytics with Large Language Models
This paper introduces ARTEMIS-DA, a framework that uses LLMs to make data analysis easier. It breaks down complex data questions into smaller steps, writes Python code to execute those steps, and then analyzes the resulting graphs to provide insights.
ARTEMIS-DA is a multi-agent system where the Planner, Coder, and Grapher agents collaborate to understand and answer data queries. The Planner interprets user requests and creates a plan. The Coder translates the plan into executable Python code. The Grapher analyzes visualizations generated by the code. This agent collaboration enables ARTEMIS-DA to handle multi-step data analysis tasks more effectively than single LLM approaches. This collaborative and modular framework allows flexibility in using different LLMs for each agent and adapts to diverse data analysis needs.